Identification of driving factors in national innovation ecosystems under the PSR framework: Based on machine learning algorithms

To address the challenge of insufficient momentum for sustainable global innovation development, a growing number of countries are elevating the cultivation of innovation ecosystems to the level of national strategy, aiming to secure discourse power and initiative in future international competition. Previously, studies have primarily focused on the conceptualization and evolutionary mechanisms of National Innovation Ecosystems (NIEs), and have extended the indicator systems of National Innovation Systems to evaluate NIEs performance. However, there remains a notable gap in applying ecological theories to construct NIEs indicator systems, as well as a lack of exploration into the driving effects of national macro-level characteristics on NIEs. Addressing this research gap, this study draws upon the food chain perspective and the quadruple helix model to propose a novel conceptual framework for understanding the interactions among actors within the NIEs. Furthermore, we introduce the Pressure-State-Response (PSR) framework to establish a system of driving factors centered on National Risk, National Openness, and National Governance. This research provides a systematic analytical tool for clarifying the interactive logic among multi-level innovation actors. The revealed differentiated driving pathways offer empirical evidence for countries to tailor innovation governance policies.